Reinforcement Learning

Researchers From Microsoft and Princeton University Find Text-Based Agents can Achieve High Scores Even in The Complete Absence of Semantics

Recently, Text-based games have become a popular testing method for developing and testing reinforcement learning (RL). It aims to build autonomous agents that can...

Researchers at Lawrence Livermore National Laboratory (LLNL) Developed a Novel Deep Learning Framework for Symbolic Regression

At the Lawrence Livermore National Laboratory (LLNL), scientists have developed a novel framework and an accompanying visualization tool that utilizes deep reinforcement learning for...

DeepMind Researchers Introduce Manipulation-Independent Representations (MIR) For Successful Cross Embodiment Visual Imitation

Recently, researchers at DeepMind have proposed manipulation-independent representations (MIR) to support successful imitation of behaviors demonstrated by previously unseen manipulator morphologies using only visual...

This California Based Company Is Utilizing AI For The Protection Of Service Members And Civilians Through An Unmanned Self-Driving Software

Shield AI is a California-based startup employing artificial intelligence to develop products that offer protection for service members and civilians. It is primarily a...

Researchers At Uber AI And Open AI Introduce Go-Explore: Cracking The Challenging Atari Games With Artificial Intelligence

Learning from rewards is an unsaid practice among all. The above is also the guiding insight behind a family of algorithms that used deep...

Google AI and UC Berkeley Introduce PAIRED: A Novel Multi-Agent Approach for Adversarial Environment Generation

The success of any machine learning technique is hugely dependent on its training data. In the case of reinforcement learning (RL), we can either...

How ‘MAB’ (Multi-Armed Bandit), A Reinforcement Learning Algorithm, Helps To Solve Ad Optimization Problem

Digital Advertising agencies cater to billions of ads on various digital platforms. However, their primary concern remains the same- Which ad will be most...

Exploring Self-Supervised Policy Adaptation To Continue Training After Deployment Without Using Any Rewards

Humans possess a remarkable ability to adapt, generalize their knowledge and use their experiences in new situations. Simultaneously, building an intelligent system with common-sense...

Introduction to Reinforcement Learning

Reinforcement learning is a field of machine learning wherein the goal is learning to perform specific actions in an environment which leads to finding...

Researchers Examine Three Intrinsic Motivation Types To Stimulate Intrinsic Objectives Of Reinforcement Learning (RL) Agents

Reinforcement learning (RL) has enabled tools to make decisions and solve complex problems in unknown environments directly from high-dimensional image inputs, such as locomotion,...

DeepMind Introduces MuZero That Achieves Superhuman Performance In Tasks Without Learning Their Underlying Dynamics

Previously, DeepMind has used reinforcement learning to teach programs to master various games such as the Chinese board game 'Go,' the Japanese strategy game...

Facebook AI Introduces ‘ReBeL’: An Algorithm That Generalizes The Paradigm Of Self-Play Reinforcement Learning And Search To Imperfect-Information Games

Most AI systems excel in generating specific responses to a particular problem. Today, AI can outperform humans in various fields. For AI to do...

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